Cost-effectiveness analysis of fluticasone furoate/umeclidinium bromide/vilanterol and umeclidinium bromide/vilanterol in the management of moderate and severe COPD in China.

OBJECTIVE: A study has analyzed the long-term cost-effectiveness of fluticasone furoate/umeclidinium bromide/vilanterol combination therapy (FF/UMEC/VI) versus umeclidinium bromide/vilanterol dual therapy (UMEC/VI) in the treatment of moderate or severe chronic obstructive pulmonary disease (COPD), providing evidence for decision-making in COPD treatment. METHODS: From the perspective of the whole society, a Markov model based on the severity of COPD was established, consisting of four states: moderate, severe, very severe, and death. The cycle of the model is three months, and the time frame of the study is 20 years. Data such as initial states, transition probabilities, costs, and utilities were collected from published literature, the National Institute for Health and Care Excellence (NICE) COPD economic report, Yaozh database, and the National Statistics Office. The discount rate is 5 %, and the willingness to pay threshold is set at three times the per capita GDP of China in 2022. TreeAge Pro 2011 was used to obtain the results of multiplication analyses, and one-way factor analysis and probability sensitivity analysis were conducted. RESULTS: The study findings demonstrate that for patients treated with FF/UMEC/VI and UMEC/VI, the 20-year treatment costs amount to $10,126.46 and $10,685.74, respectively. Similarly, the effectiveness is 32.94 quality-adjusted life years (QALYs) and 32.19 QALYs, respectively. The incremental cost-effectiveness ratio is $-745.70/QALY, which is lower than the willingness to pay threshold. The tornado plot from one-way factor analysis indicates that the first two factors impacting the results are the utility values for severe COPD of UMEC/VI and FF/UMEC/VI. Probability sensitivity analysis indicates that FF/UMEC/VI compared to UMEC/VI can be considered a more cost-effective treatment at the willingness to pay threshold of $35,806.96. CONCLUSION: The triple therapy (FF/UMEC/VI) is more affordable than dual therapy (UMEC/VI) when compared to China's three times GDP per capita criterion.

Assessment of estrogenic potential from exudates of microcystin-producing and non-microcystin-producing Microcystis by metabolomics, machine learning and E-screen assay.

Cyanobacterial blooms, often dominated by Microcystis aeruginosa, are capable of producing estrogenic effects. It is important to identify specific estrogenic compounds produced by cyanobacteria, though this can prove challenging owing to the complexity of exudate mixtures. In this study, we used untargeted metabolomics to compare components of exudates from microcystin-producing and non-microcystin-producing M. aeruginosa strains that differed with respect to their ability to produce microcystins, and across two growth phases. We identified 416 chemicals and found that the two strains produced similar components, mainly organoheterocyclic compounds (20.2%), organic acids and derivatives (17.3%), phenylpropanoids and polyketides (12.7%), benzenoids (12.0%), lipids and lipid-like molecules (11.5%), and organic oxygen compounds (10.1%). We then predicted estrogenic compounds from this group using random forest machine learning. Six compounds (daidzin, biochanin A, phenylethylamine, rhein, o-Cresol, and arbutin) belonging to phenylpropanoids and polyketides (3), benzenoids (2), and organic oxygen compound (1) were tested and exhibited estrogenic potency based upon the E-screen assay. This study confirmed that both Microcystis strains produce exudates that contain compounds with estrogenic properties, a growing concern in cyanobacteria management.

Prognostic Assessment of Colorectal Cancer Patients after Laparoscopic Surgery: A Comprehensive Evaluation of the Glasgow Prognostic Score and Fibrinogen-to-Prealbumin Ratio.

BACKGROUND Previous studies have shown that systemic inflammation and suboptimal nutritional status are associated with poor cancer prognosis. This study aims to investigate the prognostic value of preoperative Glasgow prognostic score (GPS) and fibrinogen-to-prealbumin ratio (FPR) in patients with CRC (colorectal cancer) after laparoscopic surgery. MATERIAL AND METHODS In this study, the clinical data of 112 patients with CRC who underwent laparoscopic surgery were retrospectively analyzed, and the 3-year and 5-year survival rates of these patients were evaluated. In addition, the prognostic role of preoperative FPR and GPS in CRC patients was assessed using X-tile software, Kaplan-Meier analysis, and Cox regression analysis. Receiver operating characteristic (ROC) curves were generated to assess the predictive value of FPR, GPS, and FPR-GPS for the survival of these patients. RESULTS The results revealed a significant negative correlation between high FPR, elevated GPS, and overall survival (OS) in patients with CRC. Univariate and multivariate Cox regression analyses identified GPS (HR=3.207, 95% CI: 1.746~6.126), FPR (HR=2.669, 95% CI: 1.052~6.772), and lymph node metastasis (HR=2.222, 95% CI: 1.199~4.115) as independent prognostic indicators for overall survival. The ROC analysis demonstrated that the prediction based on FPR and GPS outperformed a single indicator in accurately predicting the prognosis of CRC patients. CONCLUSIONS Combining the preoperative FPR with the GPS contributes to accurate prognosis assessment for CRC patients after laparoscopic surgery. Patients exhibiting high FPR and GPS values are associated with a worse prognosis.

Innovation network, knowledge absorption ability, and technology innovation performance--An empirical analysis of China's intelligent manufacturing industry.

Based on the social network theory, this study utilizes knowledge absorption capacity as the mediating variable and technology turbulence as the moderating variable; furthermore, it focuses on China's intelligent manufacturing industry data to explore the effect of the intelligent manufacturing enterprise innovation network on technology innovation performance and the regulating mechanism of technology turbulence. Based on the patent data obtained from Derwent Database (survey period: 2016-2020), the empirical analysis indicates the following: (1) Network relationship, network location, and network density are significantly and positively correlated with technology innovation performance; however, network size exerts no significant effect on technology innovation performance. (2) Network relationship strength, network location, and network density exert significantly positive effects on the two dimensions of knowledge absorption capacity, namely the In-degree and the Out-degree. Network size exerts no significant effect on knowledge absorption capacity. (3) Knowledge absorption capacity exerts a partial mediating effect on the relationship between innovation network and technology innovation performance. (4) The three dimensions of innovation network that exert a significant effect on technology innovation performance are positively correlated with the interaction terms of technology turbulence, which indicates that the interaction terms, namely innovation network and technology turbulence, exert a positive impact on technology innovation performance through knowledge absorption capacity, and that the moderating effect of technology turbulence exerts a role through knowledge absorption capacity. Finally, this study postulates implementations and policy proposals for enhancing the innovation performance of intelligent manufacturing enterprises.

A Predictive Decision Analytics Approach for Primary Care Operations Management: A Case Study of Double-Booking Strategy Design and Evaluation.

Primary care plays a vital role for individuals and families in accessing care, keeping well, and improving quality of life. However, the complexities and uncertainties in the primary care delivery system (e.g., patient no-shows/walk-ins, staffing shortage, COVID-19 pandemic) have brought significant challenges in its operations management, which can potentially lead to poor patient outcomes and negative primary care operations (e.g., loss of productivity, inefficiency). This paper presents a decision analytics approach developed based on predictive analytics and hybrid simulation to better facilitate management of the underlying complexities and uncertainties in primary care operations. A case study was conducted in a local family medicine clinic to demonstrate the use of this approach for patient no-show management. In this case study, a patient no-show prediction model was used in conjunction with an integrated agent-based and discrete-event simulation model to design and evaluate double-booking strategies. Using the predicted patient no-show information, a prediction-based double-booking strategy was created and compared against two other strategies, namely random and designated time. Scenario-based experiments were then conducted to examine the impacts of different double-booking strategies on clinic's operational outcomes, focusing on the trade-offs between the clinic productivity (measured by daily patient throughput) and efficiency (measured by visit cycle and patient wait time for doctor). The results showed that the best productivity-efficiency balance was derived under the prediction-based double-booking strategy. The proposed hybrid decision analytics approach has the potential to better support decision-making in primary care operations management and improve the system's performance. Further, it can be generalized in the context of various healthcare settings for broader applications.

Imaging feature-based clustering of financial time series.

Timeseries representation underpin our ability to understand and predict the change of natural system. Series are often predicated on our choice of highly redundant factors, and in fact, the system is driven by a much smaller set of latent intrinsic keys. It means that a better representation of data makes points in phase space clearly for researchers. Specially, a 2D structure of timeseries could combine the trend and correlation characters of different periods in timeseries together, which provides more clear information for top tasks. In this work, the effectiveness of 2D structure of timeseries is investigated in clustering tasks. There are 4 kinds of methods that the Recurrent Plot (RP), the Gramian Angular Summation Field (GASF), the Gramian Angular Differential Field (GADF) and the Markov Transition Field (MTF) have been adopted in the analysis. By classifying the CSI300 and S&P500 indexes, we found that the RP imaging series are valid in recognizing abnormal fluctuations of financial timeseries, as the silhouette values of clusters are over 0.6 to 1. Compared with segment methods, the 2D models have the lowest instability value of 0. It verifies that the SIFT features of RP images take advantage of the volatility of financial series for clustering tasks.

Virulence assessment of four Glaesserella parasuis strains isolated in Liaoning province of China.

Glaesserella parasuis (G. parasuis) is a part of the normal upper respiratory microbiota of healthy swine. In many studies, the serovars 1, 4, 5, and 12 of G. parasuis are considered to be highly virulent and its serovars 3, 6, 7, 9, and 11 are considered to be non-virulent. Until now, researchers have found that non-virulent strains of G. parasuis cause an increasing number of diseases. However, little is known concerning why non-virulent strains cause disease with the virulence changes. In present study, four G. parasuis strains were evaluated for their cytotoxicity property, which aims to compare their virulence. The results showed that highly virulent strains XX0306 and CY1201, as well as, non-virulent strains HLD0115 and YK1603 caused a series of pathological changes, increased lactate dehydrogenase (LDH) release, and decreased cell activity. In addition, compared to the control group, both highly and non-virulent strains showed similar trends, demonstrating that the method of classifying the virulence of G. parasuis based on its serovar is worth further deliberation. Hence, we investigated the adhesion capacity and invasion rate of G. parasuis, the results indicated that XX0306 and HLD0115 had the strongest adhesion and invasion ability, which contradicts the classification of the virulence of G. parasuis based on its serovar. The apoptosis degree induced by highly virulent strains was more intensive than non-virulent strains, as measured by annexin V and propidium iodide (PI) double staining. Through testing the expression of apoptosis-related genes Bcl-2 and Bax, we found highly virulent strains induced apoptosis by inhibiting the expression of Bcl-2.

Assessment of Response to Different Induction Chemotherapy Regimens in Locally Advanced Nasopharyngeal Carcinoma.

Purpose: To compare the short-term treatment response and survival of the three induction chemotherapy (IC) regimens, including gemcitabine and cisplatin (GP), docetaxel and cisplatin (TP), and docetaxel, cisplatin, and fluoropyrimidines (TPF) in locally advanced nasopharyngeal carcinoma (LANPC). Methods: We included stage III-IVA NPC patients who received ≥3 cycles of IC in this study. The chi-square test, multivariate logistic regression analysis, and Kaplan-Meier method were used for statistical analysis. Results: A total of 227 patients were included. The overall response rate (ORR) of the primary nasopharyngeal tumors after IC with GP, TP, and TPF was 91.9%, 83.8%, and 91.7%, respectively (P=0.729), and the ORR of the cervical lymph nodes was 94.6%, 72.3%, and 85.0%, respectively (P<0.001). For the primary nasopharyngeal tumor, there was no significant difference in the ORR among the three IC regimens. For cervical lymph nodes, patients treated with GP had significantly higher ORR compared to those treated with the TP regimen (P=0.014), and comparable ORR was found between TPF and GP regimens (P=0.161). Similar progression-free survival (PFS) (P=0.501) and overall survival (OS) (P=0.504) were found among three IC regimens. There were comparable PFS (P=0.123) and OS (P=0.478) among those with complete response (CR), partial response (PR), and stable disease (SD)/progressive disease (PD) in the primary nasopharyngeal tumors. However, patients who had CR in the primary nasopharyngeal tumor (P=0.014) and the cervical lymph nodes (P=0.022) had better PFS compared to those who had PR or SD/PD. Conclusion: GP and TPF regimens are equivalent to the TP regimen in the response to primary nasopharyngeal tumors after IC, but with better ORR in the cervical lymph nodes than the TP regimen. The response to IC may be a powerful indicator for predicting prognosis and developing individualized follow-up and treatment strategies for LANPC patients.

Combining the anion gap with the sequential organ failure assessment score to evaluate the short-term prognosis of patients in the cardiac intensive care unit.

BACKGROUND: We attempted to determine the predictive ability of the first-day Sequential Organ Failure Assessment (SOFA) score in the cardiac intensive care unit, as well as a new score combining the anion gap (AG) with the SOFA score (SOFA-AG). METHODS: Information was obtained from the Medical Information Mart for Intensive Care III (MIMIC III 1.4) database. We plotted the relationship between the maximum first-day AG and 90-day mortality after admission to the care unit. Patients were divided into five groups based on the hazard ratio (HR) and assigned scores of 0, 1, 2, 3, or 4 points. We compared the area under the curve (AUC) for the receiver-operating characteristic curve of the SOFA and that of the SOFA-AG. RESULTS: A total of 1316 patients were identified and divided into the following five groups: AG 8 to <16 mmol/L; AG 16 to <17 mmol/L; AG 17 to <19 mmol/L; AG 19 to <21 mmol/L; and AG ≥ 21 mmol/L. The SOFA-AG score had a greater AUC than the SOFA score at 7 days (0.770 vs. 0.711; P < 0.001), 14 days (0.751 vs. 0.692; P < 0.001), 28 days (0.741 vs. 0.684; P < 0.001), and 90 days (0.727 vs. 0.667; P < 0.001). CONCLUSIONS: The SOFA score showed moderate predictive value only for 7-day mortality after admission to the cardiac intensive care unit, but the SOFA-AG score had improved predictive ability for up to 90 days after admission.

Risk factor analysis and clinical decision tree model construction for diabetic retinopathy in Western China.

BACKGROUND: Diabetic retinopathy (DR) is the driving force of blindness in patients with type 2 diabetes mellitus (T2DM). DR has a high prevalence and lacks effective therapeutic strategies, underscoring the need for early prevention and treatment. Yunnan province, located in the southwest plateau of China, has a high pre-valence of DR and an underdeveloped economy. AIM: To build a clinical prediction model that will enable early prevention and treatment of DR. METHODS: In this cross-sectional study, 1654 Han population with T2DM were divided into groups without (n = 826) and with DR (n = 828) based on fundus photography. The DR group was further subdivided into non-proliferative DR (n = 403) and proliferative DR (n = 425) groups. A univariate analysis and logistic regression analysis were conducted and a clinical decision tree model was constructed. RESULTS: Diabetes duration ≥ 10 years, female sex, standing- or supine systolic blood pressure (SBP) ≥ 140 mmHg, and cholesterol ≥ 6.22 mmol/L were risk factors for DR in logistic regression analysis (odds ratio = 2.118, 1.520, 1.417, 1.881, and 1.591, respectively). A greater severity of chronic kidney disease (CKD) or hemoglobin A 1c increased the risk of DR in patients with T2DM. In the decision tree model, diabetes duration was the primary risk factor affecting the occurrence of DR in patients with T2DM, followed by CKD stage, supine SBP, standing SBP, and body mass index (BMI). DR classification outcomes were obtained by evaluating standing SBP or BMI according to the CKD stage for diabetes duration < 10 years and by evaluating CKD stage according to the supine SBP for diabetes duration ≥ 10 years. CONCLUSION: Based on the simple and intuitive decision tree model constructed in this study, DR classification outcomes were easily obtained by evaluating diabetes duration, CKD stage, supine or standing SBP, and BMI.

[Distribution Characteristics and Risk Assessment of Accumulated Heavy Metals in Bioretention Systems].

Topsoil samples (0-10 cm) from four bioretention systems with different land-use types were collected, including parking lot, roadside, residential area, and industrial park systems. The accumulation contents of As, Hg, Cd, Cr, Pb, Cu, Ni, and Zn were analyzed and evaluated, as were the influencing factors, pollution level, potential ecological risk, and human health risk. The results showed that there were significant differences in the accumulated contents of eight heavy metals. The average ω(As), ω(Hg), ω(Cd), ω(Cr), ω(Pb), ω(Cu), ω(Ni), and ω(Zn) were 8.92, 0.25, 0.10, 31.56, 14.81, 21.27, 23.69, and 62.75 mg·kg-1, respectively, and the average contents of As and Hg were 1.26 and 5.21 times the soil background values, respectively. Correlation analysis showed that the contents of the eight heavy metals were positively correlated with soil organic matter, pH value (except Hg), and phosphorus content (except As). The results of the Nemerow Comprehensive Pollution Index and Hakanson Potential Ecological Index showed that the pollution level and ecological risk of the other seven heavy metals were relatively low, whereas the pollution level and ecological risk of Hg reached the level of severe pollution and strong ecological risk, respectively. Affected by Hg, the comprehensive pollution level and ecological risk were relatively high; thus, Hg was a potential threat to the soil environment. The non-carcinogenic risks of heavy metals in the four systems were acceptable, but the carcinogenic risks were all beyond 10-6 though lower than 10-4, which indicated that these four systems had a certain carcinogenic risk, in which As was the main risk factor. Among these four land-use types, the accumulated pollutant contents, pollution levels, ecological risk, and human health risk of parking lots and roadside bioretention systems were much higher than those of residential areas and industrial parks.

A Study on the Cognition and Emotion Identification of Participative Budgeting Based on Artificial Intelligence.

Cognition and emotion exert a powerful influence on human behavior. Based on cognitive psychology and organizational behavior theory, this paper examines the role of cognition and emotion in participative budgeting and corporate performance using a questionnaire survey. The questionnaires were sent to 345 listed companies in China. The results support the hypothesis that human cognition and emotion have a positive moderating effect on the relationship between participative budgeting and corporate performance. Cognition and emotion can promote the effect of participative budgeting on corporate performance. Furthermore, according to the theory of artificial intelligence (AI), this paper designs an AI-based cognition and emotion identification system. This system can help managers identify the budget participants' cognitive and emotional states and undertake the interventions necessary to improving corporate performance.

Elements, characteristics, and performances of inter-enterprise knowledge recombination: Empirical research on green innovation adoption in China's heavily polluting industry.

Knowledge recombination has become a hot topic in green innovation adoption (GIA) research in recent years. However, previous studies have mainly discussed the knowledge recombination within a single enterprise but ignored inter-enterprise knowledge recombination (Inter-KR). In this paper, a theoretical framework of Inter-KR is developed, and the three features of Inter-KR are discussed: elements, characteristics, and performances. Multisource heterogeneous data combined with Natural language process, network analysis and econometric regression are used to analyze the above three features. Social network theory is introduced to elaborate on the influence mechanism of Inter-KR. The empirical results indicate that enterprises can effectively improve their environmental performance by participating in Inter-KR: 1) the participation of Inter-KR is significantly influenced by time and national policy; 2) further refinement and decomposition of the characteristics of inter-KR find that the comprehensiveness has a significant promoting effect on GIA. When issuing relevant policies, the government should consider the balanced development of environmental governance and enterprise innovation, and improve the GIA performance by enabling enterprises to acquire an in-depth and extensive knowledge base. In summary, this paper provides new insights for research on knowledge recombination, the literature on collaboration innovation, and green innovation adoption research.

Evaluation of the Infectious Diseases Society of America's Core Antimicrobial Stewardship Curriculum for Infectious Diseases Fellows.

BACKGROUND: Antimicrobial stewardship (AS) programs are required by Centers for Medicare and Medicaid Services and should ideally have infectious diseases (ID) physician involvement; however, only 50% of ID fellowship programs have formal AS curricula. The Infectious Diseases Society of America (IDSA) formed a workgroup to develop a core AS curriculum for ID fellows. Here we study its impact. METHODS: ID program directors and fellows in 56 fellowship programs were surveyed regarding the content and effectiveness of their AS training before and after implementation of the IDSA curriculum. Fellows' knowledge was assessed using multiple-choice questions. Fellows completing their first year of fellowship were surveyed before curriculum implementation ("pre-curriculum") and compared to first-year fellows who complete the curriculum the following year ("post-curriculum"). RESULTS: Forty-nine (88%) program directors and 105 (67%) fellows completed the pre-curriculum surveys; 35 (64%) program directors and 79 (50%) fellows completed the post-curriculum surveys. Prior to IDSA curriculum implementation, only 51% of programs had a "formal" curriculum. After implementation, satisfaction with AS training increased among program directors (16% to 68%) and fellows (51% to 68%). Fellows' confidence increased in 7/10 AS content areas. Knowledge scores improved from a mean of 4.6 to 5.1 correct answers of 9 questions (P = .028). The major hurdle to curriculum implementation was time, both for formal teaching and for e-learning. CONCLUSIONS: Effective AS training is a critical component of ID fellowship training. The IDSA Core AS Curriculum can enhance AS training, increase fellow confidence, and improve overall satisfaction of fellows and program directors.

Exploiting Operation Importance for Differentiable Neural Architecture Search.

Recently, differentiable neural architecture search (NAS) methods have made significant progress in reducing the computational costs of NASs. Existing methods search for the best architecture by choosing candidate operations with higher architecture weights. However, architecture weights cannot accurately reflect the importance of each operation, that is, the operation with the highest weight might not be related to the best performance. To circumvent this deficiency, we propose a novel indicator that can fully represent the operation importance and, thus, serve as an effective metric to guide the model search. Based on this indicator, we further develop a NAS scheme for "exploiting operation importance for effective NAS" (EoiNAS). More precisely, we propose a high-order Markov chain-based strategy to slim the search space to further improve search efficiency and accuracy. To evaluate the effectiveness of the proposed EoiNAS, we applied our method to two tasks: image classification and semantic segmentation. Extensive experiments on both tasks provided strong evidence that our method is capable of discovering high-performance architectures while guaranteeing the requisite efficiency during searching.

Relationships Among CEO Narcissism, Debt Financing and Firm Innovation Performance: Emotion Recognition Using Advanced Artificial Intelligence.

Psychological research shows that as the main component of enterprise decision-making, CEOs are not completely rational, cognitive and psychological biases often influence their decision-making process. CEO narcissism has gradually attracted academic attention. Based on upper echelon theory and subconscious theory, this paper uses advanced artificial intelligence technology to quantify CEO narcissism as a kind of emotional intelligence. Taking A-share listed companies in China from 2010 to 2019 as research objects, this paper empirically tests the impact of CEO narcissism on debt financing and innovation performance. The results show that CEO narcissism has a significant positive impact on firm innovation performance. Debt financing plays a mediating role in the relationship between CEO narcissism and firm innovation performance. CEO narcissism can have a positive impact on firm innovation performance through debt financing. Compared with non-SOEs, SOEs' CEO narcissism has a more significant positive effect on debt financing and enterprise innovation performance. The research in this paper enriches psychology and organizational management and provides a reference for an enterprise's management decisions and for investors' investment decisions.

Ascertaining an efficient eligibility cut-off for extended Medicare items for eating disorders.

OBJECTIVE: Currently eligibility for expanded Medicare items for eating disorders (excluding anorexia nervosa) require a score ⩾ 3 on the 22-item Eating Disorder Examination-Questionnaire (EDE-Q). We compared these EDE-Q "cases" with continuous scores on a validated 7-item version of the EDE-Q (EDE-Q7) to identify an EDE-Q7 cut-off commensurate to 3 on the EDE-Q. METHODS: We utilised EDE-Q scores of female university students (N = 337) at risk of developing an eating disorder. We used a receiver operating characteristic (ROC) curve to assess the relationship between the true-positive rate (sensitivity) and the false-positive rate (1-specificity) of cases ⩾ 3. RESULTS: The area under the curve showed outstanding discrimination of 0.94 (95% CI: .92-.97). We examined two specific cut-off points on the EDE-Q7, which included 100% and 87% of true cases, respectively. CONCLUSION: Given the EDE-Q cut-off for Medicare is used in conjunction with other criteria, we suggest using the more permissive EDE-Q7 cut-off (⩾2.5) to replace use of the EDE-Q cut-off (⩾3) in eligibility assessments.

Low-cost compressive sensing imaging based on spectrum-encoded time-stretch structure.

A low-cost compressive sensing imaging (CSI) system based on spectrum-encoded time-stretch (SETS) structure involving cascaded Mach-Zehnder Interferometers (MZIs) for spectral domain random mixing (also known as the optical random pattern generator) is proposed and experimentally demonstrated. A proof-of-principle simulation and experiment is performed. A mode-locked laser with a repetition rate of 50MHz and low-cost cascaded MZIs as the key devices enable fast CSI system. Data compression ratio from 6% to 25% are obtained using proposed CSI based SETS system. The proposed design solves the big data issue in the traditional time-stretch system. It has great potential in fast dynamic phenomena with low-cost and easy-access components.

Does green industrial policy promote the sustainable growth of polluting firms? Evidences from China.

In this research, the impact of municipal green industry policies in 15 cities on the economic and environmental performance of local companies was evaluated, and the policy coordination mechanism was studied. As a dual-goal policy mix, the green industrial policy has been used by Chinese municipal governments to solve the dilemma between the economic growth and environmental mitigation. However, the quantitative evaluation of these green industrial policy trials remains limited. To address this issue, the policy evaluation in this research applied sewage discharge data and operation data of 22,670 Chinese textile firms from 1998 to 2013 from Chinese Environmental Statistics Database. Fixed-effect regression analysis and dynamic difference-in-differences (DID) approach were used to assess the dual-faceted impacts of green industrial policies and their subtypes, as well as the continuity of these impacts. The findings suggest that adopting a dual-objective green industrial policy is an effective approach to encourage heavy-polluting firms to develop in a more balanced and sustainable way. From dynamic DID analysis, these green industrial policies have continuity effects on both chemical oxygen demand discharge intensity and annual revenue of firms after implementation and the general impacts can last for at least 4 years. The study also reveals the heterogeneity in the impacts of three different subtypes of green industrial policy. The technology-push policy subtype can quickly reduce environmental discharge without compromising economic development, while demand-pull policy subtype has a slow effect on the improvement of environmental performance. The balanced policy subtype can promote enterprises to achieve both optimal performance of economy and environment, although the efficiency of balanced policy subtype is between two subtypes. Generally, this research provides reliable basis for the implementation of green industrial policies in developing countries and provides certain inspiration for the enriching of green industry policy theory.

Analysis of risk factors for carotid intima-media thickness in patients with type 2 diabetes mellitus in Western China assessed by logistic regression combined with a decision tree model.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in patients with type 2 diabetes (T2DM). Carotid intima-media thickness (CIMT) is considered a preclinical stage of atherosclerosis. Therefore, it is necessary to identify the related risk factors for CIMT to facilitate the early prevention of CVD. Previous studies have shown that visceral fat area (VFA) is a risk factor for T2DM and CVD. However, few studies have focused on the effects of VFA on CIMT associated with T2DM. Moreover, considering that the body fat distribution shows regional and racial heterogeneity, the purpose of this study was to investigate the predictive value of VFA and other risk factors for CIMT associated with T2DM in Western China. METHODS: In a cross-sectional study, a total of 1372 patients with T2DM were divided into the CIMT (-) group (n = 965) and the CIMT (+) group (n = 407) based on CIMT values. In addition to the univariate analyses, logistic regression analysis and a decision tree model were simultaneously performed to establish a correlation factor model for CIMT. RESULTS: Univariate analyses showed that sex, smoking status, age, heart rate, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, weight, body mass index (BMI), waist circumference, hip circumference, waist-hip ratio, VFA, subcutaneous fat area, and the levels of 2-h C-peptide, serum creatinine, urea nitrogen and uric acid were significantly different between the two groups (all p < 0.05). Smoking, increased VFA, female sex and increased BMI were risk factors in the logistic regression analyses (OR = 5.759, OR = 1.364, OR = 2.239, OR = 1.186, respectively). In the decision tree model, smoking was the root node, followed by sex, waist circumference, VFA and chronic kidney disease (CKD) in order of importance. CONCLUSIONS: In addition to smoking, sex and BMI, VFA has a significant effect on CIMT associated with T2DM in the Chinese Han population in Western China. In addition, the decision tree model could help clinicians make more effective decisions, with its simplicity and intuitiveness, making it worth promoting in future medical research.Trial registration ChiCTR, ChiCTR1900027739. Registered 24 November 2019-Retrospectively registered, http://www.chictr.org.cn/index.aspx.